Applied Science Manager, Stores-ads Science

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Applied Science Manager to lead a team focused on understanding and optimizing how advertising creates value for shoppers and selling partners, particularly as the shopping experience evolves towards agentic commerce. The role involves leading research, designing experiments, developing optimization algorithms, and translating research into production systems, with a strong emphasis on causal inference, economic modeling, and applied ML.

What you'd actually do

  1. In this role, you will lead a team of scientists, setting the technical vision and science roadmap for ads impact measurement and optimization.
  2. You will design experiments that identify the causal mechanisms through which advertising drives shopper engagement, advertiser value, and marketplace outcomes.
  3. You will develop optimization algorithms that integrate these causal signals into production and business decision-making, in close partnership with engineering and product teams across the organization.
  4. You will lead the research and communicate findings and recommendations to senior leadership through written narratives that connect technical science to business strategy.
  5. You will hire and develop future science leaders, think strategically, set ambitious roadmaps in highly ambiguous problem spaces, and foster a culture that values both intellectual depth and production impact.

Skills

Required

  • 4+ years of applied research experience
  • 3+ years of scientists or machine learning engineers management experience
  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Knowledge of ML, NLP, Information Retrieval and Analytics
  • Experience programming in Java, C++, Python or related language

Nice to have

  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
  • Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows

What the JD emphasized

  • lead our Ads Impact initiative
  • partner with leading scientists and academic researchers
  • develop novel methods to encode causal and economic reasoning into AI systems
  • evolves from traditional search toward LLM-powered, agentic commerce
  • deep expertise in causal inference and experimental design
  • strong applied ML skills
  • engineering judgment to translate research into production systems
  • hire and develop future science leaders
  • set ambitious roadmaps in highly ambiguous problem spaces

Other signals

  • The role will partner with leading scientists and academic researchers to measure these effects through large-scale causal experimentation, and develop novel methods to encode causal and economic reasoning into AI systems that optimize the shopping experience.
  • This role requires deep expertise in causal inference and experimental design, combined with strong applied ML skills and the engineering judgment to translate research into production systems.
  • We are looking for an Applied Science Manager to lead our Ads Impact initiative. This team owns the science of understanding and optimizing how advertising creates value for shoppers and selling partners.
  • as Amazon's shopping experience evolves from traditional search toward LLM-powered, agentic commerce, the fundamental mechanisms through which advertising creates value are changing.